class_docstr: This is the matplotlib based GUI for a single analysis
  It assumes the analysis is simple image data (this could be abstracted)
docstr: Start the imshow plot by showing dummy daya - a blank image
docstr_tok: ["Start","the","imshow","plot","by","showing","dummy","daya","-","a","blank","image"]
code: def init_plot(self, data, image_dimensions):
      """Start the imshow plot by showing dummy daya - a blank image"""
      self.image_dimensions = image_dimensions
      self.data = data
  
      # Display initial empty composite
      dummydata = np.zeros(image_dimensions, dtype=np.float32)
      self.composite_digit = np.zeros(
          (image_dimensions[0] * image_dimensions[1],)
      )
      self.display_img = self.ix.imshow(
          dummydata,
          interpolation="bilinear",
          cmap="gray",
          vmin=0,
          vmax=255,
      )
  
file_path: nptsne/demos/ExtendedHSNEDemo/CompositeImageViewer.py
imports: import numpy
  import matplotlib.pyplot
  import matplotlib.style
  from matplotlib.backends.backend_qt5agg import FigureCanvas
  from matplotlib.figure import Figure
label_desc: Use image node_id 2 for calling the CompositeImageViewer obj's underlying member method code with example usage: obj.init_plot(data, image_dimensions) without return types